Robust, fast, and adaptive splitting schemes for nonlinear doubly-degenerate diffusion equations
Ayesha Javed, Koondanibha Mitra, Iuliu Sorin Pop

TL;DR
This paper introduces robust, fast, and adaptive splitting schemes for nonlinear doubly-degenerate diffusion equations, demonstrating improved stability and convergence properties through theoretical analysis and numerical experiments.
Contribution
It develops and analyzes new splitting and linearization schemes, including adaptive strategies, for challenging nonlinear degenerate parabolic equations, with proven convergence and enhanced stability.
Findings
The M- and M-adaptive schemes are more stable than the Newton scheme.
The adaptive M-scheme outperforms other schemes with quadratic convergence.
Convergence is proven even in the double-degenerate case.
Abstract
We consider linear iterative schemes for the time-discrete equations stemming from a class of nonlinear, doubly-degenerate parabolic equations. More precisely, the diffusion is nonlinear and may vanish or become multivalued for certain values of the unknown, so the parabolic equation becomes hyperbolic or elliptic, respectively. After performing an Euler implicit time-stepping, a splitting strategy is applied to the time-discrete equations. This leads to a formulation that is more suitable for dealing with the degeneracies. Based on this splitting, different iterative linearization strategies are considered, namely the Newton scheme, the L-scheme, and the modified L-scheme. We prove the convergence of the latter two schemes even for the double-degenerate case. In the non-degenerate case, we prove that the scheme is contractive, and the contraction rate is proportional to a non-negative…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Numerical Methods in Computational Mathematics · Numerical methods for differential equations · Differential Equations and Numerical Methods
